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Two ways of biasing galaxy formation

Catelan, Paolo and Porciani, Cristiano and Kamionkowski, Marc (2000) Two ways of biasing galaxy formation. Monthly Notices of the Royal Astronomical Society, 318 (3). L39-L44. ISSN 0035-8711. doi:10.1046/j.1365-8711.2000.04023.x.

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We calculate the galaxy bispectrum in both real and redshift space, adopting the most common prescriptions for local Eulerian biasing and the Lagrangian evolving-bias model. We show that the two biasing schemes make measurably different predictions for these clustering statistics. The Eulerian prescription implies that the galaxy distribution depends only on the present-day local mass distribution, while its Lagrangian counterpart relates the current galaxy distribution to the mass distribution at an earlier epoch when galaxies first formed. Detailed measurement of the galaxy bispectrum (of its reduced amplitude) can help establish whether galaxy positions are determined by the current mass distribution or an earlier mass distribution.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Porciani, Cristiano0000-0002-7797-2508
Kamionkowski, Marc0000-0001-7018-2055
Additional Information:© 2000 RAS. Accepted 2000 September 14. Received 2000 August 27; in original form 2000 April 14. We thank Sabino Matarrese for discussions. The anonymous referee improved the presentation of these results. CP is supported by a Golda Meir Fellowship. This work was supported at Caltech in part by the DoE, NSF and NASA.
Funding AgencyGrant Number
Hebrew University of JerusalemUNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
Subject Keywords:galaxies: statistics - large-scale structure of Universe
Issue or Number:3
Record Number:CaltechAUTHORS:20200519-170818755
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Official Citation:Paolo Catelan, Cristiano Porciani, Marc Kamionkowski, Two ways of biasing galaxy formation, Monthly Notices of the Royal Astronomical Society, Volume 318, Issue 3, November 2000, Pages L39–L44,
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103336
Deposited By: Rebecca Minjarez
Deposited On:20 May 2020 21:21
Last Modified:16 Nov 2021 18:20

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